Cardiac arrhythmia analysis and characterization are used for the management of cardiac disorders and irregularities. Cardiac electrophysiological (EP) activities can be used to sense, monitor and diagnose cardiac arrhythmia and pathology related abnormality. For example, P wave disorders for atrial fibrillation (AF) and ST segment changes for myocardial ischemia and infarction. However, cardiac pathology related electrophysiological signal and waveform changes are small and difficult to extract, especially in the early stages of a cardiac abnormality or event. Additionally, known clinical methods for ECG or intra-cardiac electrogram analysis may not efficiently diagnose a signal waveform singularity or diagnose irregular changes caused by cardiac arrhythmia, especially sub-waveform changes in electrophysiological signals.
Early arrhythmia recognition and characterization, such as of myocardial ischemia and infarction, is desirable for rhythm management and treatment of cardiac disorders and irregularities. Known systems use waveform morphologies and time domain parameter analysis of depolarization and repolarization, including P wave, QRS complex, ST segment, T wave, for cardiac arrhythmia monitoring and identification. However, known systems are often subjective and time-consuming, and require expertise and clinical experience for accurate interpretation and proper cardiac rhythm management. Known systems fail to provide sufficient information on cardiac electrophysiological function and activity interpretation, tissue mapping and arrhythmia localization.
Additionally, known systems typically focus on time (amplitude, latency) or frequency (power, spectrum) domain changes and analysis. This may fail to capture and characterize small signal changes in a partial portion (P wave, QRS complex, ST segment) of a cardiac activity signal and are usually invisible in a signal waveform or need extensive clinical expertise to correctly diagnose. In cardiac arrhythmia cases (especially in an early stage, such as myocardial ischemia, ventricular tachycardia), signal changes are hidden inside electrograms. In early stages of cardiac arrhythmia, pathology and event related signal changes are small and not easy to detect. Known systems typically fail to qualitatively and quantitatively capture and characterize such small changes, and predict a pathological trend. Known systems typically fail to identify in real time a growing trend of a cardiac arrhythmia, such as a pathology trend from low risk to medium, and then to high risk (severe and fatal) rhythm (especially for an arrhythmia, such as VT (ventricular tachycardia) and myocardial infarction (MI)). Known systems for cardiac arrhythmia calculation and evaluation generate inaccurate and unreliable data and results because of unwanted noise and artifacts. Environmental noise and patient movement artifacts, such as electrical interference, can distort a waveform and make it difficult to detect R wave and ST segment elevation accurately, and generate false alarms. A system according to invention principles addresses these deficiencies and related problems.